Elbow arthroscopy in acute injuries
Bibliographic record
Abstract
PURPOSE: Arthroscopy of the elbow has become a standard treatment option for many indications. The purpose of this article is to review literature concerning the use of arthroscopy for acute elbow injuries. METHODS: The main medical literature databases were searched for articles on the use of elbow arthroscopy in acute injuries. A total of 13 publications relevant to the topic were included. The Coleman methodology score was used to assess the methods of each article. RESULTS: All published articles have been case reports or retrospective case series. In fracture treatment, arthroscopy has been used in the treatment of displaced radial head, coronoid and capitellum fractures in adults and displaced radial neck and lateral humeral condyle fractures in children with good results. Endoscopic techniques have been used in distal biceps rupture and medial avulsion of the triceps. And also new techniques have been developed for the treatment of intra-articular soft-tissue lesions like rupture of the radial ulnohumeral ligament complex. One of the 13 studies analyzed was considered of good quality, 5 of moderate quality and all others of poor quality with inconsistent methodology and outcomes. CONCLUSION: The range of treatments using elbow arthroscopy in acute injuries is expanding and brings new controversies and challenges. Single reports of arthroscopically treated bony and soft-tissue injuries of the elbow showed satisfactory results. However, further randomized prospective studies are needed to evaluate their safety and efficacy compared with open 'gold standard' techniques. LEVEL OF EVIDENCE: IV.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".